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Sequential (two-stage) estimation of linear panel-data models

Author

Listed:
  • Sebastian Kripfganz

    (University of Exeter Business School)

Abstract
I present the new Stata command xtseqreg, which implements sequential (two-stage) estimators for linear panel-data models. In general, the conventional standard errors are no longer valid in sequential estimation when the residuals from the first stage are regressed on another set of (often time-invariant) explanatory variables at a second stage. xtseqreg computes the analytical standard-error correction of Kripfganz and Schwarz (2015), which accounts for the first-stage estimation error. The command can be used to fit both stages of a sequential regression or either stage separately. OLS and 2SLS estimation are supported, as well as one-step and two-step "difference"-GMM and "system"-GMM estimation in the spirit of Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (1998), with flexible choice of the instruments and weighting matrix. Available postestimation statistics include the Arellano–Bond test for absence of autocorrelation in the first-differenced errors and Hansen's J-test for the validity of the overidentifying restrictions. While I do not intend to introduce xtseqreg as a competitor for existing commands, it can mimic part of their behavior. In particular, xtseqreg can replicate results obtained with xtdpd and xtabond2. In that regard, I will illustrate some pitfalls in the estimation of dynamic panel models.

Suggested Citation

  • Sebastian Kripfganz, 2017. "Sequential (two-stage) estimation of linear panel-data models," German Stata Users' Group Meetings 2017 03, Stata Users Group.
    • Handle: RePEc:boc:dsug17:03
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    References listed on IDEAS

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